Target Tracking Approximation Algorithms Based on Particle Filters and near-Linear Curve Simplified Optimization in WSN

Abstract:

In order to process target tracking approximation with unknown motion state models beforehand in a two-dimensional field of binary proximity sensors, the algorithms based on cost functions of particle filters and near-linear curve simple optimization are proposed in this paper. Through moving target across detecting intersecting fields of sensors sequentially, cost functions are introduced to solve target tracking approximation and velocity estimation which is not similar to traditional particle filters that rely on probabilistic assumptions about the motion states. Then a near-linear curve geometric approach is used to simplify and easily describe target trajectories that are below a certain error measure. The validity of our algorithms is demonstrated through simulation results.

• Periodical: Applied Mechanics and Materials (Volumes 128-129)
• Pages: 1079-1084
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.128-129.1079
• Online since: October 2011
• Authors: Xiang Gao, Yin Tang Yang, Duan Zhou, Jian Xian Zhang, Chang Chun Chai
• Keywords: Cost Function, Particle Filter (PF), Target Tracking

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